Time Correlated Single Photon Counting Anindya Datta Department of - - PowerPoint PPT Presentation

Time Correlated Single Photon Counting

Anindya Datta Department of Chemistry Indian Institute of Technology Bombay Powai, Mumbai 400 076

Fluorescence Decay Following Pulsed Excitation

   

 

       

 

        t exp F t F t N t F t exp N t N

* * *

Multiple independent decay pathways: Multiexponential decays Where N*(t) = Population of the excited state at time t F*(t) = Fluorescence intensity at time t

   

      



i i

t a F t F  exp

Fluorescence Lifetime and the Depopulation Rates

      

NR R

k 1 k

• Window to excited state dynamics

Photoisomerization, Excited State Proton Transfer, Charge Transfer, Exciplexes, Energy Transfer

• Microenvironment sensitive

Protein folding, Microheterogeneous media

• Imaging and Microscopy

Radiative Nonradiative kR kNR

Schematics of the Instrument

PS: Power supply, DL: Diode laser, P: Polariser CFD: Constant fraction discriminator TAC: Time to amplitude converter MCA: Multichannel annalyser

CFD CFD Sample chamber Mono- chromator Delay Stop Start TAC Computer with MCA Short Laser Pulse DL P S Sync. Trigger

TBX-04

IBH Data Station Out P P

Time Correlated Single Photon Counting

The essence of TCSPC

CFD CFD Sample chamber Mono- chromator Delay Stop Start TAC Computer with MCA Short Laser Pulse DL P S Sync. Trigger

TBX-04

IBH Data Station Out P P

• TAC range: Time for which TAC waits for

a STOP

• Number of channels

Constant Fraction Discrimination

CFD CFD Sample chamber Mono- chromator Delay Stop Start TAC Computer with MCA Short Laser Pulse DL P S Sync. Trigger

TBX-04

IBH Data Station Out P P

Timing jitter = 50 ps for CFD, 1 ns for LED

Data Analysis: Iterative Reconvolution

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' dt ' t P ' t t F t F

D





  Finite pulse width: Convolution



D

F

L

F



P(t′) = Impulse function at time t′ F(t‐t′) = Intensity at time t, from Exponential decay with origin at time t′ Range of t′ = Determined by shape of pulse

   

 

       

 

        t exp F t F t N t F t exp N t N

* * *

Data Analysis: Iterative Reconvolution

     

' dt ' t P ' t t F t F

D





 

Data Analysis: Iterative Reconvolution

P(t’) t’ t t‐t’ F(t‐t’)P(t’)

     

' dt ' t P ' t t F t F

D





 

Data Analysis: Iterative Reconvolution

t The Guess Fitting Function is Convoluted with the Instrument Response Function and the Function thus generated is compared with the observed Decay

Goodness of Fit

Reduced χ2: Y(i) = Experimentally obtained data at point no. i FD(i) = Fitting data after convolution N = Number of data points. P = Number of parameters Reduced χ2 should be equal to 1 for a good fit Weighted Residuals: Deviation at each point can be determined

R i

   Y i    F

D i

 

 i

 

 2  1 N  p Y i

  F

D i

 

 i

 

       

N



2

 

) i ( Y i  

 2  R i

 

2 i



Global analysis of TCSPC data

Intensity Wavelength

Steady State Spectrum

3 ns 7 ns

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                   

2 2 1 1

exp exp   t a t a F t F

3 ns 7 ns Global parameters Wavelength independent Local Parameters Depend on wavelength Global 2 = Average value of local 2

Life beyond Multiexponential decays

Heterogeneous environments

• Stretched exponential function
• Distribution of lifetimes

I(t ) = I0 exp(‐t/τ )β  provides a measure of heterogeneity

Rouvière N, Gallay J. 2000. Cell Mol Biol 46(5):1113–1131.

Time resolved emission spectra

Intensity Wavelength

Steady State Spectrum TCSPC

Multiexponential decay ai and i

Iss(λ)

Intensity Wavelength

t t’ Iss(λ′ ) TRES

Isoemissive point: Two state process

• J. Chem. Phys. 2001, 115, 7094; J. Phys. Chem. A 2001, 105, 1767

Intensity Wavelength

Area Normalize t’ time

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